IoT & Cloud Infrastructure Engineer

This is a fully remote position, open to applicants in South Korea.

📋 Description

• Design, develop, and maintain firmware for wearable sensing devices.

• Establish reliable communication and data streaming between devices and cloud services to synchronize vision and tactile data.

• Architect and manage AWS infrastructure utilizing EC2, S3, Lambda, and IoT Core.

• Create APIs, ingestion services, and Python data pipelines for efficient and dependable high-throughput processing.

• Deploy, monitor, and maintain the device fleet and capture setups remotely at real-world data collection sites.

• Transform field-related issues into engineering solutions.

• Diagnose problems across firmware and cloud deployments.

• Collaborate with hardware, ML, and data teams to establish system requirements.

• Assist in testing, documentation, and ongoing enhancement of the data collection infrastructure.

• Occasional travel to collection sites may be necessary.

⛳️ Requirements

• A minimum of 4 years of engineering experience in embedded systems and cloud environments.

• Proficient embedded and firmware skills: C/C++, RTOS, microcontrollers, real-time systems, sensor integration, and low-level programming.

• Practical experience with AWS: EC2, S3, Lambda, IoT Core, as well as high-throughput, dependable data pipelines.

• Strong software engineering capabilities in Python or a similar language: APIs, data streaming services, and hardware-to-cloud integration.

• Solid understanding of networking, security best practices, performance optimization, monitoring, and logging.

• Excellent debugging skills across hardware, firmware, and cloud layers.

• A Bachelor's degree or higher in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience.

• Proficient in English.

• Knowledge of Korean or Mandarin is highly advantageous.

• Experience with robotics, tactile or force sensing, wearables, or IoT devices is a plus.

• Familiarity with building real-world data collection systems is beneficial.

• Exposure to ML data pipelines or datasets for robotic learning is preferred.

• Experience in deploying and supporting hardware in field environments is advantageous.

🏝️ Benefits

• Become part of an early-stage team at the forefront of Physical AI, one of the fastest-growing sectors in technology.

• Take ownership of a vital system from end to end, encompassing device firmware to cloud infrastructure.

• Your work will directly influence datasets that train next-generation robotic manipulation models.

• Experience high ownership, rapid iteration, and real-world impact from day one.